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N8n Marketplace Analyzer

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from $0.50 / 1,000 results

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N8n Marketplace Analyzer

N8n Marketplace Analyzer

Advanced n8n workflow scraper with analytics & ML training data. Get top nodes, categories, pricing insights, and fine-tuning datasets. Unlike basic scrapers, provides 10x value with analysis. Perfect for content creators, ML engineers & researchers. 1-10K workflows. By n8n community expert.

Pricing

from $0.50 / 1,000 results

Rating

5.0

(2)

Developer

LIAICHI MUSTAPHA

LIAICHI MUSTAPHA

Maintained by Community

Actor stats

2

Bookmarked

41

Total users

2

Monthly active users

3 months ago

Last modified

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🚀 n8n Marketplace Intelligence & Analytics

The most comprehensive n8n workflow analyzer on Apify – Go beyond basic scraping with built-in analytics, professional insights, and ML training data generation.

Apify Actor Price


🎯 Why This Actor is Different

Most n8n scrapers just collect data and stop there. This actor goes further:

FeatureBasic ScrapersThis Actor
Scrape workflows
Advanced analytics
ML training data
Creator insights
Complexity metrics
Professional reports

Perfect for: Content creators, ML engineers, market researchers, product teams, and automation experts.


⚡ Key Features

🔍 Smart Scraping

  • Collect 1 to 10,000 workflows from n8n marketplace
  • Optional category filtering (AI, DevOps, Marketing, etc.)
  • Rate-limited async scraping (API-friendly)
  • Automatic pagination with deduplication
  • Exponential backoff retry (3 attempts per page)
  • Real-time progress reporting in Apify UI

📊 Advanced Analytics

Get comprehensive insights automatically:

  • Top 30 most-used nodes with usage percentages
  • Top 15 categories distribution
  • Pricing analysis (free vs paid breakdown)
  • Complexity metrics (simple to very complex)
  • Top 20 creators by workflow count
  • Most viewed workflows with engagement data

🤖 ML Training Data

Generate fine-tuning datasets in multiple formats:

  • Alpaca format (Llama, Mistral compatible)
  • OpenAI format (GPT fine-tuning ready)
  • 4,000+ training examples from real workflows
  • Clean, structured, ready to use

📈 Professional Output

All data structured and export-ready:

  • Clean JSON format
  • Normalized fields
  • Comprehensive metadata
  • Multiple export options

💡 Use Cases

📚 Content Creation

Find trending workflows → Analyze patterns → Create tutorials

Example: Discover that "AI + Telegram" workflows get 10x more views → Create tutorial series on AI chatbots

🤖 Machine Learning

Scrape workflows → Generate training data → Fine-tune LLM

Example: Build an AI that generates n8n workflows from natural language descriptions

📊 Market Research

Scrape quarterly → Compare trends → Strategic insights

Example: Track which integrations are growing fastest to guide product decisions

🛠️ Product Development

Analyze workflow patterns → Identify user needs → Build solutions

Example: See that 70% of workflows use HTTP Request → Prioritize API features


📂 Output Data

1️⃣ Dataset (Structured Workflow Data)

Each workflow includes:

{
"id": 123,
"name": "AI Chatbot Workflow",
"description": "Build a Telegram bot using OpenAI...",
"totalViews": 50000,
"price": null,
"nodes": [
{
"name": "n8n-nodes-base.telegram",
"displayName": "Telegram",
"categories": ["Communication"]
}
],
"workflowCategories": [
{"name": "AI"},
{"name": "Communication"}
],
"user": {
"username": "creator123",
"name": "John Doe",
"verified": true
}
}

Download as: JSON, CSV, or Excel from the Dataset tab


2️⃣ Key-Value Store (Analysis & ML Data)

📈 analysis - Comprehensive Metrics

{
"metadata": {
"total_workflows": 1000,
"analysis_date": "2025-01-15T10:30:00Z"
},
"top_nodes": [
{"node": "HTTP Request", "count": 730, "percentage": 73.0},
{"node": "Code", "count": 520, "percentage": 52.0}
],
"top_categories": [
{"category": "AI", "count": 320},
{"category": "DevOps", "count": 180}
],
"pricing_analysis": {
"free_workflows": 860,
"paid_workflows": 140,
"free_percentage": 86.0,
"average_price": 12.50
},
"complexity_analysis": {
"average_nodes": 8.5,
"distribution": {
"simple_1_5": {"count": 400, "percentage": 40.0},
"medium_6_10": {"count": 350, "percentage": 35.0}
}
},
"top_creators": [
{
"username": "n8n_master",
"workflow_count": 45,
"total_views": 250000,
"verified": true
}
],
"top_viewed": [
{
"name": "Build Your First AI Agent",
"views": 150000,
"url": "https://n8n.io/workflows/123"
}
]
}

🤖 training_data_alpaca - ML Training Data (Alpaca Format)

[
{
"instruction": "Create an n8n workflow for: AI Email Assistant\n\nDescription: Automatically categorize and respond to emails using AI",
"input": "",
"output": "{\n \"nodes\": [\n {\"type\": \"Gmail Trigger\"},\n {\"type\": \"OpenAI Chat Model\"},\n {\"type\": \"Gmail\"}\n ]\n}"
}
]

🤖 training_data_openai - ML Training Data (OpenAI Format)

For GPT fine-tuning via OpenAI API



📸 Example Output

What You'll Get After Running

When your actor finishes, you'll find data in two places:


1️⃣ Dataset Tab - Raw Workflow Data

Location: Run → Dataset tab

Sample workflow item:

{
"id": 6270,
"name": "Build Your First AI Agent",
"description": "Learn how to build an AI agent that can understand natural language, access tools, and make decisions...",
"totalViews": 156789,
"price": null,
"createdAt": "2024-03-15T10:30:00.000Z",
"updatedAt": "2024-12-01T15:45:00.000Z",
"nodes": [
{
"name": "n8n-nodes-base.telegram",
"displayName": "Telegram Trigger",
"nodeCategories": [
{"name": "Communication"},
{"name": "Trigger"}
]
},
{
"name": "@n8n/n8n-nodes-langchain.agent",
"displayName": "AI Agent",
"nodeCategories": [
{"name": "AI"},
{"name": "LangChain"}
]
},
{
"name": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"displayName": "OpenAI Chat Model",
"nodeCategories": [
{"name": "AI"},
{"name": "Language Models"}
]
}
],
"workflowCategories": [
{"name": "AI"},
{"name": "Communication"},
{"name": "AI Agent"}
],
"user": {
"username": "n8n_creator",
"name": "John Doe",
"verified": true,
"avatar": "https://gravatar.com/..."
}
}

↓ Download as:

  • JSON file
  • CSV spreadsheet
  • Excel workbook

2️⃣ Key-Value Store - Analysis & Insights

Location: Run → Key-Value Stores → default → analysis

Sample analysis output:

{
"metadata": {
"total_workflows": 1000,
"analysis_date": "2025-01-15T14:30:00.000Z",
"scraper_version": "1.0.0"
},
"top_nodes": [
{
"node": "HTTP Request",
"count": 730,
"percentage": 73.0
},
{
"node": "Code",
"count": 520,
"percentage": 52.0
},
{
"node": "Set",
"count": 480,
"percentage": 48.0
},
{
"node": "IF",
"count": 450,
"percentage": 45.0
},
{
"node": "OpenAI Chat Model",
"count": 320,
"percentage": 32.0
}
],
"top_categories": [
{"category": "AI", "count": 320},
{"category": "DevOps", "count": 180},
{"category": "Marketing", "count": 165},
{"category": "Communication", "count": 140},
{"category": "Data Processing", "count": 125}
],
"pricing_analysis": {
"free_workflows": 860,
"paid_workflows": 140,
"free_percentage": 86.0,
"paid_percentage": 14.0,
"average_price": 12.50,
"price_range": {
"min": 5.00,
"max": 49.00
}
},
"complexity_analysis": {
"average_nodes": 8.5,
"min_nodes": 2,
"max_nodes": 45,
"distribution": {
"simple_1_5": {
"count": 400,
"percentage": 40.0
},
"medium_6_10": {
"count": 350,
"percentage": 35.0
},
"complex_11_20": {
"count": 180,
"percentage": 18.0
},
"very_complex_20plus": {
"count": 70,
"percentage": 7.0
}
}
},
"top_creators": [
{
"username": "n8n_master",
"name": "Sarah Johnson",
"workflow_count": 45,
"total_views": 250000,
"verified": true
},
{
"username": "automation_pro",
"name": "Mike Chen",
"workflow_count": 38,
"total_views": 180000,
"verified": true
},
{
"username": "workflow_wizard",
"name": "Emma Davis",
"workflow_count": 32,
"total_views": 145000,
"verified": false
}
],
"top_viewed": [
{
"name": "Build Your First AI Agent",
"views": 156789,
"price": null,
"creator": "n8n_creator",
"url": "https://n8n.io/workflows/6270"
},
{
"name": "Automated Social Media Manager",
"views": 142500,
"price": 19.99,
"creator": "marketing_guru",
"url": "https://n8n.io/workflows/5834"
},
{
"name": "Email Processing with AI",
"views": 128000,
"price": null,
"creator": "ai_specialist",
"url": "https://n8n.io/workflows/4921"
}
]
}

↓ Download from Key-Value Store as JSON


3️⃣ ML Training Data (Optional)

Location: Run → Key-Value Stores → default → training_data_alpaca

When enabled (generateMLData: true), you'll get:

[
{
"instruction": "Create an n8n workflow for: AI Email Assistant\n\nDescription: Automatically categorize and respond to emails using AI",
"input": "",
"output": "{\n \"nodes\": [\n {\n \"name\": \"Gmail Trigger\",\n \"type\": \"Gmail Trigger\",\n \"category\": [\"Communication\", \"Trigger\"]\n },\n {\n \"name\": \"OpenAI\",\n \"type\": \"OpenAI Chat Model\",\n \"category\": [\"AI\", \"Language Models\"]\n },\n {\n \"name\": \"Gmail\",\n \"type\": \"Gmail\",\n \"category\": [\"Communication\"]\n }\n ],\n \"node_count\": 3,\n \"node_types\": [\"Gmail Trigger\", \"OpenAI Chat Model\", \"Gmail\"]\n}"
},
{
"instruction": "Create an n8n workflow for: Social Media Scheduler\n\nDescription: Schedule and post content across multiple social media platforms",
"input": "",
"output": "{\n \"nodes\": [\n {\n \"name\": \"Schedule Trigger\",\n \"type\": \"Schedule Trigger\",\n \"category\": [\"Core Nodes\", \"Trigger\"]\n },\n {\n \"name\": \"Google Sheets\",\n \"type\": \"Google Sheets\",\n \"category\": [\"Productivity\"]\n },\n {\n \"name\": \"Twitter\",\n \"type\": \"Twitter\",\n \"category\": [\"Communication\", \"Social Media\"]\n },\n {\n \"name\": \"LinkedIn\",\n \"type\": \"LinkedIn\",\n \"category\": [\"Communication\", \"Social Media\"]\n }\n ],\n \"node_count\": 4,\n \"node_types\": [\"Schedule Trigger\", \"Google Sheets\", \"Twitter\", \"LinkedIn\"]\n}"
}
]

↓ Ready for fine-tuning Llama 3, Mistral, or GPT!


📊 Visual Guide

After your actor runs, you'll see:

Run #12345 (Succeeded)
├── 📊 Dataset (1,000 items)
│ └── Download as JSON/CSV/Excel
├── 🗂️ Key-Value Stores
│ ├── analysis.json ← Analytics
│ ├── training_data_alpaca.json ← ML data (Alpaca)
│ └── training_data_openai.jsonl ← ML data (OpenAI)
└── 📝 Log
└── Execution details

🎯 Quick Access

To download your data:

  1. Go to your run page
  2. Click "Dataset" tab → Download workflows
  3. Click "Key-Value Stores" tab → Download analysis
  4. Export format: Choose JSON, CSV, or Excel

💡 What You Can Do With This Data

Dataset (Raw workflows):

  • ✅ Import into spreadsheet
  • ✅ Build workflow library
  • ✅ Feed into database
  • ✅ Create dashboards

Analysis (Insights):

  • ✅ Create reports
  • ✅ Identify trends
  • ✅ Guide content strategy
  • ✅ Support business decisions

ML Training Data:

  • ✅ Fine-tune LLMs
  • ✅ Build AI assistants
  • ✅ Train workflow generators
  • ✅ Create recommendation systems

⚙️ Input Configuration

Analysis Mode

Choose your level of depth:

ModeDescriptionUse Case
scrape_onlyJust workflow dataQuick data collection
scrape_and_analyzeData + insights ⭐Most common use case
full_with_mlEverything + ML dataAI/ML projects

Parameters

{
"mode": "scrape_and_analyze",
"maxWorkflows": 1000,
"category": "AI",
"generateMLData": false
}
ParameterTypeDefaultDescription
modeStringscrape_and_analyzeAnalysis mode (see above)
maxWorkflowsInteger1000Max workflows to scrape (1-10,000)
categoryStringnullOptional category filter (e.g., "AI")
generateMLDataBooleanfalseGenerate ML training datasets

🎓 Example Inputs

Quick Start (50 workflows)

{
"mode": "scrape_only",
"maxWorkflows": 50
}

Full Analysis (1,000 workflows)

{
"mode": "scrape_and_analyze",
"maxWorkflows": 1000
}

Category-Specific with ML Data

{
"mode": "full_with_ml",
"maxWorkflows": 500,
"category": "AI",
"generateMLData": true
}

Maximum Analysis (All Workflows)

{
"mode": "scrape_and_analyze",
"maxWorkflows": 10000
}

💰 Pricing

$0.50 per 1,000 workflows scraped

What You Get for $0.50:

  • ✅ 1,000 complete workflow records
  • ✅ Comprehensive analysis included
  • ✅ All insights and metrics
  • ✅ Optional ML training data

Cost Examples:

  • 50 workflows: ~$0.03
  • 500 workflows: ~$0.25
  • 1,000 workflows: $0.50
  • 5,000 workflows: $2.50

Compare to Basic Scrapers ($0.25/1K):

  • ❌ Data only
  • ❌ No analysis
  • ❌ No ML data
  • ❌ No insights

This actor: 2x the price, 10x the value! 🎯


🤖 API & Automation

Trigger this actor programmatically and integrate with:

  • n8n (meta!)
  • Make.com
  • Zapier
  • Custom scripts
  • Cron jobs

Node.js Example:

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('YOUR_USERNAME/n8n-marketplace-analyzer').call({
mode: 'scrape_and_analyze',
maxWorkflows: 1000
});
const dataset = await client.dataset(run.defaultDatasetId).listItems();
console.log(dataset.items);

Python Example:

from apify_client import ApifyClient
client = ApifyClient('YOUR_API_TOKEN')
run = client.actor('YOUR_USERNAME/n8n-marketplace-analyzer').call(
run_input={
'mode': 'scrape_and_analyze',
'maxWorkflows': 1000
}
)
dataset = client.dataset(run['defaultDatasetId']).list_items()
print(dataset.items)

cURL Example:

curl -X POST https://api.apify.com/v2/acts/YOUR_USERNAME~n8n-marketplace-analyzer/runs \
-H "Authorization: Bearer YOUR_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"mode": "scrape_and_analyze",
"maxWorkflows": 1000
}'

📊 Performance & Efficiency

  • Fast: Scrapes 1,000 workflows in ~2 minutes (async HTTP)
  • Efficient: Low compute usage (no browser needed)
  • Reliable: Exponential backoff retry (3 attempts per page, up to 3 consecutive failures before abort)
  • Deduplicated: Workflow IDs tracked to prevent duplicates across pages
  • Scalable: Handle 1 to 10,000 workflows easily
  • Cost-effective: Uses minimal Apify compute units

🎯 Real-World Applications

For Content Creators

Weekly Workflow:

  1. Run actor with maxWorkflows: 500
  2. Analyze top trending workflows
  3. Identify content gaps
  4. Create tutorial series
  5. Repeat weekly

Result: Always know what's hot in n8n community

For ML Engineers

Dataset Creation:

  1. Run with full_with_ml mode
  2. Download training_data_alpaca.json
  3. Fine-tune Llama 3 or Mistral
  4. Build AI workflow generator
  5. Publish as SaaS

Result: AI-powered n8n workflow assistant

For Market Researchers

Quarterly Analysis:

  1. Scrape all workflows (10,000)
  2. Export analysis to CSV
  3. Create visualizations
  4. Compare to last quarter
  5. Present insights to stakeholders

Result: Data-driven automation strategy

For Product Teams

Feature Prioritization:

  1. Analyze most-used nodes
  2. Identify integration gaps
  3. Study workflow complexity
  4. Plan roadmap
  5. Validate with data

Result: Build what users actually need


🛠️ Technical Details

Built With:

  • Apify SDK - Actor framework
  • Python 3.13 - Core language
  • aiohttp - Async HTTP client
  • asyncio - Async operations

Data Sources:

  • n8n.io public API
  • n8n marketplace workflows
  • Creator profiles
  • Usage statistics

Output Formats:

  • JSON (structured)
  • CSV (spreadsheets)
  • Excel (business reports)

🔄 Workflow Integration

Use with n8n (Ironic!)

Trigger: Schedule (weekly)
Action: Run Apify Actor
Action: Get Dataset Items
Action: Analyze Trends
Action: Send Slack Notification

Use with Make.com

Schedule → Apify → Google Sheets → Email Report

Use with Zapier

New Actor Run → Get Results → Update Airtable

📈 Success Stories

"Used this to identify trending workflow patterns for my n8n tutorial series. Views increased 3x!"

— Content Creator

"Generated 5,000 training examples and fine-tuned an LLM to generate workflows. Game changer!"

— ML Engineer

"Quarterly reports from this actor guide our entire automation strategy."

— Product Manager


💬 Support & Custom Development

Need Help?

Custom Services Available:

  • 🎨 Custom analysis reports
  • 🤖 ML model fine-tuning
  • 🔧 Bespoke scrapers
  • 📊 Data visualization
  • 🚀 Automation consulting

🎓 About the Creator

Built by MuLIAICHI, an AI Engineer and n8n community contributor with:

  • 📚 Popular tutorial website (n8nlearninghub.com)
  • 🔬 Open-source projects on GitHub
  • 🤖 Expertise in LLM fine-tuning
  • 🎯 Deep n8n automation knowledge

Other Projects:

  • n8n Workflow Analysis Project - Open-source analysis of 6,000+ workflows
  • FreelancerBot Pro - AI-powered freelancing assistant
  • n8n tutorial series - Weekly educational content

🚀 Get Started Now

  1. Try it free with Apify's free tier ($5 credit)
  2. Run a test with 50 workflows
  3. See the insights in minutes
  4. Scale up as needed

Quick Start:

{
"mode": "scrape_and_analyze",
"maxWorkflows": 100
}

Click "Try for Free" above to start! 🎉


⭐ Why Choose This Actor?

Most comprehensive - More features than any competitor ✅ Professional quality - Production-ready output ✅ Great value - 10x features for 2x price ✅ Active support - Built by community expert ✅ Proven results - Based on 6,000+ workflow analysis ✅ Regular updates - Maintained and improved


📋 Comparison Table

FeatureBasic ScrapersThis ActorPremium
Scrape workflows
Category filtering
Analytics
ML training data
Creator insights
Complexity analysis
Price per 1K$0.25$0.50$2.00+
Value Score⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐


📜 License & Terms

  • License: Apache-2.0
  • Terms: Follow Apify Terms of Service
  • Usage: Respect n8n's API rate limits
  • Data: Public n8n marketplace data only

🎉 Ready to Get Insights?

Try it now with 50 free workflows!

This actor transforms raw workflow data into actionable intelligence. Perfect for anyone serious about n8n automation.


⭐ Star this actor if you find it useful!

💬 Questions? Issues? Contact us anytime!


Last updated: January 2025 Version: 1.0.0 Maintained by: MuLIAICHI (mustaphaliaichi@gmail.com)